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Modelling Credit Risk for Innovative SMEs: the Role of Innovation Measures

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Listed author(s):
  • Chiara Pederzoli
  • Grid Thoma
  • Costanza Torricelli

    ()

Abstract

Small-medium enterprises (SMEs) encounter financial constraints when they try to obtain credit from banks. These constraints are particularly severe for innovative SMEs. Thus, developing models for innovative SMEs that provide reliable estimates of their probabilities of default (PD) is important because the PDs can also serve as ratings. We examine the role of innovative assets such as patents in credit risk modelling due to their signaling value. Specifically, we add to a logit model two innovation-related variables in order to account for both the dimension and the value of the patent portfolio. Based on a unique data set of innovative SMEs with default years of 2005–2008, we show that, although the value of the patent portfolio always reduces the PD, its dimension reduces the firm’s riskiness only if coupled with an appropriate equity level. Copyright Springer Science+Business Media New York 2013

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File URL: http://hdl.handle.net/10.1007/s10693-012-0152-0
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Article provided by Springer & Western Finance Association in its journal Journal of Financial Services Research.

Volume (Year): 44 (2013)
Issue (Month): 1 (August)
Pages: 111-129

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Handle: RePEc:kap:jfsres:v:44:y:2013:i:1:p:111-129
DOI: 10.1007/s10693-012-0152-0
Contact details of provider: Web page: http://www.springer.com

Web page: http://westernfinance.org/

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Order Information: Web: http://www.springer.com/journal/10693

Keywords: Innovative small-medium enterprises; Default probability; Patent value; R&D productivity; G21; G32; C25; O34;

Find related papers by JEL classification:

  • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
  • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
  • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
  • O34 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Intellectual Property and Intellectual Capital

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Cited by:

  1. Elisabetta Gualandri & Valeria Venturelli, 2013. "The financing of Italian firms and the credit crunch: findings and exit strategies," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 13101, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
  2. Andreeva, Galina & Calabrese, Raffaella & Osmetti, Silvia Angela, 2016. "A comparative analysis of the UK and Italian small businesses using Generalised Extreme Value models," European Journal of Operational Research, Elsevier, vol. 249(2), pages 506-516.
  3. C. Pederzoli & C. Torricelli, 2013. "Efficiency and unbiasedness of corn futures markets: new evidence across the financial crisis," Applied Financial Economics, Taylor & Francis Journals, vol. 23(24), pages 1853-1863, December.
  4. Stefano Cosma & Elisabetta Gualandri, 2014. "The sovereign debt crisis: the impact on the intermediation model of Italian banks," BANCARIA, Bancaria Editrice, vol. 2, pages 48-60, February.

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